# ReadMe for: Can (Thin) Populism be manipulated without manipulating Host Ideology? Evidence from a conjoint validation approach# Journal of Experimental Political Science# Author: Fabian G. Neuner# Data filesAll data was originally collected by the author and is available at https://doi.org/10.7910/DVN/JIUPOU (Neuner 2025). There are two datasets in the repository:Prolific_US_Raw.csv: Raw data for Samples 1 and 2Prolific_UK_Raw.csv: Raw data for Sample 3# VariablesThe survey instruments can be accessed at https://doi.org/10.17605/OSF.IO/NUAVW. Information on the coding of all demographic variables is provided in script_02 and script_03. Conjoint attributes:The code in script_04 creates long-format data for conjoint analyses. Each dataset includes the following conjoint attributes:Anti-elitism: See Table 1 in manuscript for levels.People-centrism: See Table 1 in manuscript for levels.Filler: See Table 1 in manuscript for levels.Partisanship*: Democrat or Republican * Important Note: The partisanship attribute was only displayed to respondents in Sample 2 but the variable also exists in Samples 1 and 3. Respondents did not see this attribute in those samples and code in script_04 thus changes the levels to �not shown� in those cases.Outcome variables: People-centrism binary: choice_1 (with a �pair� prefix for each of the six conjoint trials)People-centrism rating: people_1 (rating for profile 1) and people_2 (rating for profile 2) Anti-elitism binary: choice_2 (with a �pair� prefix for each of the six conjoint trials)Anti-elitism rating: elite_1 (rating for profile 1) and elite_2 (rating for profile 2)Immigration binary: choice_3 (with a �pair� prefix for each of the six conjoint trials)Immigration rating: immigration_1 (rating for profile 1) and immigration_2 (rating for profile 2)Conservatism binary: choice_4 (with a �pair� prefix for each of the six conjoint trials)Conservatism rating*: ideology_1 (rating for profile 1) and ideology_2 (rating for profile 2)* Note: the question wording for the Conservatism rating variables differs in the US and UK samples (see Online Appendix Section H).Each of the above variables exist with a s1_, s2_, or a s3_ prefix indicating which sample the variable applies to.Each of the rating outcomes also has a �pair� prefix for each of the six conjoint trials.# R codeThe scripts in the replication archive were originally run on a Mac OS (Sonoma 14.6.1) with R version 4.4.1 (2024-06-14).There are six scrips in the repository: script_01: Loads required packagesscript_02: Data cleaning and variable construction using Prolific_US_Raw.csvscript_03: Data cleaning and variable construction using Prolific_UK_Raw.csvscript_04: Prepares long-format data for all conjoint analysesscript_05: Produces all main manuscript resultsscript_06: Produces all supplementary material resultsIn order to produce all results presented in the manuscript and supplementary materials, please run all scripts in the above order as script_02, script_03, and script_04 produce datasets that are required for script_05 and script_06.# Working directory To replicate the analyses, the working directory needs to be set as the replication folder that contains the above datasets and scripts. All scripts should be run sequentially in the correct order.# Packagestidyverse (version 2.0.0)ggplot2 (version 3.5.1)psych (version 2.4.12)egg (version 0.4.5)cjoint (version 2.1.1)cregg (version 0.3.7)*car (version 3.1-3)modelsummary (version 2.3.0)* Note: If package "cregg" is not installed, it can be downloaded at https://cran.r-project.org/src/contrib/Archive/cregg/cregg_0.4.0.tar.gz . After downloading, place the file in working directory and run: install.packages("Path to downloaded file", repos = NULL, type = "source")# ContactFor questions, please contact Fabian Neuner at fneuner@asu.edu